1. Field of the Invention
This invention relates generally to water distribution networks, and more particularly, to software tools for designing such networks.
2. Background Information
Water distribution systems represent a large portion of a water utility's asset and investment. Optimal design of a water distribution system is ideal and it is important for a company to make intelligent decisions on its investment in this asset. Over the years, an optimal design has traditionally been associated with a design that involves the least cost. The minimum cost warrants a lower investment. However, from a perspective of systematic analysis, the lowest cost does not necessarily yield an optimal return on the water utility company's investment.
More specifically, one of the ultimate goals of a system analysis is to maximize the net benefits (i.e. benefits—cost) of the system. The yield of a system can be measured by either its value or net benefit. For a water distribution system, the true value or the net benefit is a reliable water supply service having adequate quantity and good quality. For a water company, it is desirable to plan for the provision of sufficient water supply for the community not only at the present time, but also over a reasonable future-planning horizon. During this planning period, the amount of water required for a system or the demand can be estimated, but this has typically been performed with some uncertainty.
In many cases, a municipal body or town council, for example, will determine that a water distribution network is to be extended to include a new subdivision. In such a case the new subdivision is to be supplied with water carrying capacity. In many cases, the existing system must be evaluated to determine the effects that the new system will have on the existing system. For example, the decisions must be made whether the supply capacity will be enough not only to supply the new subdivision, but also to maintain the capacity or demand that exists with respect to the old system. Thus, the town council needs to determine how best to extend the network to include the new subdivision in order to service the new subdivision, and how or whether the existing portions of the system should be improved.
System design, by its nature, is governed by multiple criteria or objectives. Cost is often a primary criterion in design because, if the benefit is fixed, the least cost design results in the maximum net benefit. Conventionally, this assumption has been the foundation of the least cost design approach. However, the least cost design normally results in a minimum capacity for a water distribution system. A minimum cost design model is usually formulated to search for the least cost solution (pipe sizes) while satisfying the hydraulic constraints such as required junction pressures, maximum pipe flow velocities and hydraulic gradients for a given demand condition over a planning horizon. The cost is given as a tabular or numerical function of pipe diameters. To locate the minimum cost solution, the optimization search process is led to the minimum pipe sizes, thus a minimum capacity.
However, the least capacity is not necessarily the preferable solution for a long term systematic planning due to the uncertainty of the future demand. Some extra pipe capacity is beneficial to allow the supply to grow into its full capacity within a planning horizon and to account for uncertainty in demands and the need for reliability in case of outages. The pipe flow capacity needs to be considered as another criteria to evaluate the design solution, and not constrained to the minimum pipe sizes. Thus, the optimal design is no longer a single objective (minimizing cost), but a multi-objective (minimizing cost and maximizing flow capacity) optimization problem.
Prior techniques have allowed a user to evaluate the costs of the system or evaluate pipe flow capacities and make determinations on a trial and error basis about the best way to either build a new system or rehabilitate portions of an existing system. However, prior techniques have not given the user the capability of a trade off or a multi-objective design. In other words, a user may have a particular budget, and thus needs to maintain costs within that budget, yet would like to have a suggested pressure or flow at a particular location or overall in the system.
There remains a need therefore for a tool for designing a water distribution network that provides the user with a multi-objective approach for designing the water distribution system.
There remains a further need for a system that allows for designing a new system or rehabilitating an old system, which takes into account many trial solutions, based on either cost or capacity benefit.
In addition, when considering the benefits of a design and rehabilitation, an engineer usually takes into account the potential hydraulic performance improvement (the hydraulic benefit) and access hydraulic capacity (capacity benefit) and pipe rehabilitation improvement (rehabilitation benefit). There are times when one of these is more important than the other. A user might, in some circumstances, decide to design a system that focuses on pressure improvement so that the benefit of hydraulic performance, in which case is measured using junction pressure improvements. A flow benefit or capacity benefit might be the focus of a different engineer in another system. Prior techniques have not provided the user with the ability to determine which of these benefit functionalities are to be the focus of a rehabilitation of a system. There remains a need therefore for a software tool for the design of a water distribution network that allows a user to select between benefit objectives in such a manner that pressure benefits, flow benefits, rehabilitation benefits or unitized benefits can be identified as priorities in the design or rehabilitation of the water distribution network.
It is thus an object of the present invention to provide a software tool for the design of a water distribution network that allows a user to select the criterion for determining the optimal solutions based on the benefits to the system or rehabilitation.
In some cases, demand changes occur following initial pipe installation (Walski 2001). Thus, it is difficult to precisely forecast the demand, when installing the pipes and other components in the first instance. In order that the optimal design is produced for the maximum value or benefit for a water distribution system, an engineer must be able to determine the maximum net benefit—a surrogate of optimal capacity for the design.
System design, by its nature, is governed by multiple criteria or objectives. Cost is often a primary criterion in design because, if the benefit is fixed, the least cost design results in the maximum net benefit. Conventionally, this assumption has been the foundation of the least cost design approach. However, the least cost design normally is based on a minimum capacity for a water distribution system. A minimum cost design model is usually formulated to search for the least cost solution while satisfying the hydraulic constraints such as required junction pressures, maximum pipe flow velocities and hydraulic gradients for a given demand condition over a planning horizon. The cost is given as a tabular or numerical function of pipe diameters. To locate the minimum cost solution, the optimization search process is led to the minimum pipe sizes.
However, the least capacity is not necessarily a preferable solution for a water distribution system, particularly for long term systematic planning. This is due, in part, to the uncertainty of future demands. Some extra pipe capacity is beneficial to allow the supply to grow into its full capacity within a planning horizon and to account for uncertainty in demands and the need for reliability in case of outages. The pipe flow capacity needs to be considered as another criteria to evaluate the design solution, and not constrained to the minimum pipe sizes. Thus, the optimal design is no longer a single objective (minimizing cost), but a multi-objective (minimizing cost and maximizing flow capacity) optimization problem.
Up to the present, there have not been effective multi-objective optimizations algorithms. In order to solve multi-objective optimizations, the problem was transformed into a single-objective optimization problem by using two adjustments including a weighted sum of objectives and a ε-constraint methods. The weighted sum approach applies a set of weighting factors to all the objectives and sums up the weighted objectives to construct a composite single objective. But, this solution is not typically reliable unless the weights are correctly chosen which can be difficult. The weighted-objective approach is in fact a simplified approach for multi-objective optimization. It converts multi-objectives into a single objective and solves the problem with a single optimization paradigm. It is not able to locate the optimal tradeoff solutions (so-called Pareto optimal solutions) of all the original objectives.
The constraint method chooses one of the objective functions as the single objective, and treats the other objective functions as constraints. Each of the constraints is limited to a prescribed value. The optimal solution, however, depends on the pre-defined constraint limits. Thus, in both cases used in prior techniques there must be a contrived set of values that may or may not give rise to a realistic set of solutions.
There remains a need, therefore, for the design of a water distribution system that allows multi-objective approach for designing an optimized cost-benefit water distribution system, without lumping together single objectives to be solved for multiobjectives.
It is thus an object of the present invention to provide a water distribution design method and system that readily allows for multi-objective optimization, including the objectives of minimizing costs while maximizing various benefit characteristics of the network being designed or rehabilitated.